Getting Started with Amazon Bedrock

Amazon Bedrock lowers the barrier to building generative AI applications by providing unified, serverless access to leading foundation models without managing infrastructure. This guide walks through the fundamentals of getting started with Bedrock — from enabling model access and running first prompts to understanding how Bedrock fits into modern AWS architectures and real-world AI development workflows.

Foundation Models (FMs) in 2024: A Practical Guide to Choosing the Right Model

Foundation models are evolving faster than most teams can evaluate them. This practical guide cuts through benchmark hype to explain how to actually choose the right model for real-world workloads — balancing capability, cost, latency, reasoning quality, and operational constraints. Instead of chasing the “best” model, the post focuses on matching models to use cases and building a repeatable decision framework for production AI systems.

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs): A Technical Deep Dive

Generative AI and large language models have rapidly moved from research curiosity to foundational software infrastructure. This technical deep dive breaks down how modern GenAI systems actually work — from transformers and embeddings to prompting, retrieval-augmented generation, and production architecture patterns — helping engineers move beyond hype and understand the mechanics, tradeoffs, and real capabilities behind today’s AI systems.

Terraform Building Blocks and Best Practices

Terraform becomes truly powerful once you move beyond basic resource definitions and start designing reusable, scalable infrastructure patterns. This post explores the core building blocks of Terraform — modules, variables, state management, and environment structure — along with practical best practices for organizing infrastructure code, avoiding common pitfalls, and building maintainable cloud platforms that scale with teams and environments.

Understanding Terraform

Terraform introduced a fundamental shift in how infrastructure is built and operated — treating cloud environments as versioned, reproducible code instead of manual configuration. This post explains Terraform from first principles, breaking down core concepts like infrastructure as code, state management, providers, and execution workflows to help engineers understand not just how Terraform works, but why it became a cornerstone of modern cloud engineering.